| Presentation | 2006-12-13 An efficient extension of stochastic proximity embedding in distance geometry problem Hiroyuki KASHIMA, Shinji DOI, Sadatoshi KUMAGAI, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Distance geometry problem is the problem to determine the molecular structure from the distance data between atoms. We apply SPE (Stochastic Proximity Embedding) method to distance geometry problem of huge molecular like protein from a data set of upper and lower distance bounds. We propose an efficient extension of SPE to determine the structure when only a few distance bounds data are known. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Distance geometry / Nuclear Magnetic Resonance / protein-structure determination / optimization method |
| Paper # | NLP2006-96 |
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| Conference Information | |
| Committee | NLP |
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| Conference Date | 2006/12/6(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Nonlinear Problems (NLP) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An efficient extension of stochastic proximity embedding in distance geometry problem |
| Sub Title (in English) | |
| Keyword(1) | Distance geometry |
| Keyword(2) | Nuclear Magnetic Resonance |
| Keyword(3) | protein-structure determination |
| Keyword(4) | optimization method |
| 1st Author's Name | Hiroyuki KASHIMA |
| 1st Author's Affiliation | Department of Electrical Engineering, Graduate School of Engineering, Osaka University() |
| 2nd Author's Name | Shinji DOI |
| 2nd Author's Affiliation | Department of Electrical Engineering, Graduate School of Engineering, Osaka University |
| 3rd Author's Name | Sadatoshi KUMAGAI |
| 3rd Author's Affiliation | Department of Electrical Engineering, Graduate School of Engineering, Osaka University |
| Date | 2006-12-13 |
| Paper # | NLP2006-96 |
| Volume (vol) | vol.106 |
| Number (no) | 413 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |